The objective of this course is to teach the students the basic concepts of standard geostatistics. Students will learn, in the course, the main theoretical concepts related to the spatial interpolation of attributes using geostatistics. The students will also work on computer programs to practice the theoretical concepts. The course is developed with theoretical classes, under the professor responsibility, and also with practical laboratories that the student must run out of the theoretical class time. Following the theoretical classes there are some exercises that the student must work on and report the answers to the professor. During the course the students must work, also, in one sample set of interest with the geostatistics concepts and techniques and present to the professor, as well as to the other students, their work results. Finally, the students must write reports about these results.
Ana Cristina Marinho da Costa
Weekly - Available soon
Total - Available soon
Portuguese. If there are Erasmus students, classes will be taught in English
Deutsch, C. V.; Journel, A. G., 1998. Geostatistical Software Library and User¿s Guide. Oxford University Press, New York, USA.
Goovaerts, P., 1997. Geostatistics for Natural Resources Evaluation. Oxford University Press, Inc, New York, USA.
Isaaks, E. H.; Srivastava, R. M., 1989. An Introduction to Applied Geostatistics. Oxford University Press, Inc, New York, USA.
Fotheringham A.S., Brunsdon C., Charlton M. (2002) Geographically Weighted Regression: the analysis of spatially varying relationships. Wiley, Chichester, UK.
Soares, A. 2000. Geoestatística para as Ciências da Terra e do Ambiente. Instituto Superior de Técnico, IST Press. Lisboa, Portugal.
The curricular unit is based on theoretical lectures and practical application of methods using software applications, such as Excel and ArcGIS. The practical component is geared towards solving problems and exercises, including discussion and interpretation of results. A variety of instructional strategies will be applied, including lectures, slide show demonstrations, step-by-step instructions on using the Geostatistical Analyst functionality of the ArcGIS software, questions and answers.
1. Three individual reports with the answers to the proposed problems (10% of final grade each);
2. Exam (25% of final grade)
3. Oral presentation of the students' project (10% of final grade);
4. Article reporting the work done related to the project (35% of final grade).
The project can be developed individually or in groups of 2 students.
1.1. Initial concepts and motivation
2. Exploratory data analysis
2.1. Univariate description
2.2. Bivariate description
2.3. Spatial description
3. Deterministic methods for spatial interpolation
3.1. General concepts
3.2. Thiessen polygons (Voronoi maps)
3.3. Inverse distance weighting
3.4. Validation and cross-validation
4.1. Spatial continuity analysis
4.2. Models of spatial continuity
5. Univariate geostatistics
5.1. Geostatistics estimation concepts
5.2. Simple kriging
5.3. Universal kriging
5.4. Ordinary kriging
6. Multivariate geostatistics
6.1. Bivariate spatial description
6.2. Modelling a coregionalization
6.3. Simple kriging with varying local means
6.4. Kriging with an external drift
6.5. Cokriging and collocated cokriging
Programs where the course is taught:
- Specialization in Information Analysis and Management
- Specialization in Risk Analysis and Management
- Specialization in Knowledge Management and Business Intelligence
- Specialization in Information Systems and Technologies Management
- Specialization in Marketing Intelligence
- Specialization in Marketing Research and CRM
- Specialization in Knowledge Management and Business Intelligence – Working Hours Format
- Specialization in Information Systems and Technologies Management - Working Hours Format
- Specialization in Marketing Intelligence - Working Hours Format
- Master of Geographic Information Systems and Science
- Post-Graduation in Information Analysis and Management
- Post-Graduation Risk Analysis and Management
- PostGraduate in Smart Cities
- PostGraduate in Geographic Information Systems and Science
- PostGraduate in Data Science for Marketing
- PostGraduate in Digital Enterprise Management
- PostGraduate Digital Marketing and Analytics
- PostGraduate in Information Systems Governance
- PostGraduate in Information Management and Business Intelligence in Healthcare
- Post-Graduation in Knowledge Management and Business Intelligence
- Post-Graduation Information Systems and Technologies Management
- Post-Graduation in Marketing Intelligence
- Post-Graduation Marketing Research e CRM
- PostGraduate in Enterprise Information Systems